Estimating the Number of Solutions in Program Space Using Random Sampling

Created by W.Langdon from gp-bibliography.bib Revision:1.9209

@InProceedings{Craine:2026:UKCI,

• author = "Benjamin J. Craine and Barry Porter",
• title = "Estimating the Number of Solutions in Program Space Using Random Sampling",
• booktitle = "25th UK Workshop on Computational Intelligence (UKCI 2026)",
• year = "2026",
• address = "Coventry University",
• month = "9--11 " # sep,
• keywords = "genetic algorithms, genetic programming, grammatical evolution, Program Space, Probability, Grammar, PMLB, MonteCarlo",
• size = "6 pages",
• abstract = "We attempt to predict the number of programs in a finite program space that meet a specification. The utility of being able to predict this is to provide a quantifiable measurement to how difficult a very specific search problem over program space is.",
• notes = "'Finding a Solution by Random Chance' exhaustive search. scipy curve_fit. consistently under estimated the size of O. Fig 2: Number of Optimums, estimates versus truth.

  To be published after the workshop

  https://ukci2026.coventry.ac.uk/",

}

Genetic Programming entries for Benjamin J Craine Barry Porter

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